h<JdZddlmZddlZddlmZddlmZmZm Z m Z ddl m Z ddl mZmZmZmZmZddlmZmZdd lmZdd lmZmZdd lmZmZmZdd lm Z dd l!m"Z"m#Z#ddl$m%Z%m&Z&m'Z'm(Z(ddl)m*Z*ddl+m,Z,ddl-m.Z.m/Z/ddl0m1Z1e dddGdde1Z2ddZ3y)z2Chain that just formats a prompt and calls an LLM.) annotationsN)Sequence)AnyOptionalUnioncast) deprecated)AsyncCallbackManagerAsyncCallbackManagerForChainRunCallbackManagerCallbackManagerForChainRun Callbacks)BaseLanguageModelLanguageModelInput) BaseMessage)BaseLLMOutputParserStrOutputParser)ChatGeneration Generation LLMResult) PromptValue)BasePromptTemplatePromptTemplate)RunnableRunnableBindingRunnableBranchRunnableWithFallbacks)DynamicRunnable)get_colored_text) ConfigDictField)Chainz0.1.17z&RunnableSequence, e.g., `prompt | llm`z1.0)since alternativeremovalc>eZdZUdZed+dZded< ded< dZd ed <ee Z d ed < dZ ded< ee Z ded<eddZed,dZed,dZ d- d.dZ d- d/dZ d- d0dZ d- d1dZ d- d2dZ d- d3dZ d- d3dZed4dZd5dZ d- d6d Zd-d7d!Zd-d7d"Z d- d8d#Z d- d9d$Z d- d:d%Z! d;d&Z" d- d:d'Z#ed4d(Z$edLLMChaina^Chain to run queries against LLMs. This class is deprecated. See below for an example implementation using LangChain runnables: .. code-block:: python from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import PromptTemplate from langchain_openai import OpenAI prompt_template = "Tell me a {adjective} joke" prompt = PromptTemplate( input_variables=["adjective"], template=prompt_template ) llm = OpenAI() chain = prompt | llm | StrOutputParser() chain.invoke("your adjective here") Example: .. code-block:: python from langchain.chains import LLMChain from langchain_community.llms import OpenAI from langchain_core.prompts import PromptTemplate prompt_template = "Tell me a {adjective} joke" prompt = PromptTemplate( input_variables=["adjective"], template=prompt_template ) llm = LLMChain(llm=OpenAI(), prompt=prompt) boolcy)NTselfs R/var/www/html/eduruby.in/venv/lib/python3.12/site-packages/langchain/chains/llm.pyis_lc_serializablezLLMChain.is_lc_serializableNsrpromptzSUnion[Runnable[LanguageModelInput, str], Runnable[LanguageModelInput, BaseMessage]]llmtextstr output_key)default_factoryr output_parserTreturn_final_onlydict llm_kwargsforbid)arbitrary_types_allowedextrac.|jjS)zJWill be whatever keys the prompt expects. :meta private: )r0input_variablesr+s r- input_keyszLLMChain.input_keyshs {{***r/cP|jr |jgS|jdgS)z=Will always return text key. :meta private: full_generation)r7r4r+s r- output_keyszLLMChain.output_keysps*  ! !OO$ $!233r/NcR|j|g|}|j|dSN run_managerr)generatecreate_outputsr,inputsrFresponses r-_callzLLMChain._callzs. ==&{=C""8,Q//r/c*|j||\}}|r|jnd}t|jtr*|jj ||fd|i|j S|jjdd|i|j jtt|d|i}g}|D]K}t|tr|jt|g0|jt|gMt|S z Generate LLM result from inputs.rEN callbacksstop)message)r2) generationsr*) prep_prompts get_child isinstancer1rgenerate_promptr9bindbatchrlistrappendrrr r, input_listrFpromptsrPrOresultsrRress r-rGzLLMChain.generates  ))*+)N /:K))+ dhh 1 2+488++$//    $((--=T=T__=CC w  ) $ /1  ;C#{+""N3$?#@A""JC$8#9:  ; [11r/cpK|j||d{\}}|r|jnd}t|jtr2|jj ||fd|i|j d{S|jjdd|i|j jtt|d|id{}g}|D]K}t|tr|jt|g0|jt|gMt|S777gwrN) aprep_promptsrTrUr1ragenerate_promptr9rWabatchrrYrrZrrrr[s r- ageneratezLLMChain.agenerates0 #000UU /:K))+ dhh 1 2222$//   & C4C4??CJJ w  ) $  /1  ;C#{+""N3$?#@A""JC$8#9:  ; [11'V  s6D6D/A"D6<D2=AD6 D4 A#D62D64D6cd}t|dk(rg|fSd|dvr|dd}g}|D]}|jjDcic]}||| }}|jjd i|}t |j d} d| z} |r|j | d|jd|vr|d|k7r d} t| |j|||fScc}w zPrepare prompts from inputs.NrrPgreenzPrompt after formatting:  )endverbosez=If `stop` is present in any inputs, should be present in all.r* lenr0r> format_promptr to_stringon_textrj ValueErrorrZ r,r\rFrPr]rJkselected_inputsr0 _colored_text_textmsgs r-rSzLLMChain.prep_promptss  z?a t8O Z] "a=(D #F59[[5P5PQq&)|QOQ.T[[..AAF,V-=-=-?IM0=@E##EtT\\#JF6Nd$:U o% NN6 " #}Rs CcKd}t|dk(rg|fSd|dvr|dd}g}|D]}|jjDcic]}||| }}|jjd i|}t |j d} d| z} |r&|j | d|jd{d|vr|d|k7r d} t| |j|||fScc}w79wrfrkrqs r-razLLMChain.aprep_promptss  z?a t8O Z] "a=(D #F59[[5P5PQq&)|QOQ.T[[..AAF,V-=-=-?IM0=@E!))%T4<<)PPPF6Nd$:U o% NN6 " #}R QsAC. C'A C.2C,3:C.cZtj||j|j}|j dd|i|j } |j ||}|j|}|jd|i|S#t$r}|j|d}~wwxYwz0Utilize the LLM generate method for speed gains.Nr\)namerEoutputs) r configurerOrjon_chain_startget_namerG BaseExceptionon_chain_errorrH on_chain_endr,r\rOcallback_managerrFrKer{s r-applyzLLMChain.applys +44  NN LL  '55  : &6  }}Z[}IH%%h/  )W!56    & &q )  sB B*B%%B*cKtj||j|j}|j dd|i|j d{} |j ||d{}|j|}|jd|id{|S7N74#t$r }|j|d{7d}~wwxYw76wry) r r|rOrjr}r~rdrrrHrrs r-aapplyzLLMChain.aapplys 099  NN LL  -;;  : &<   !^^JK^PPH%%h/&& 7';<<< Q ,,Q/ / /   =s`ACB$CB(1B&2B(6'CCC&B(( C1C CC  CCc|jSNr4r+s r-_run_output_keyzLLMChain._run_output_keys r/c|jDcgc]+}|j|jj|d|i-}}|jr(|Dcgc]}|j||ji}}|Scc}wcc}w)zCreate outputs from response.rA)rRr4r6 parse_resultr7)r, llm_result generationresultrs r-rHzLLMChain.create_outputs s)44  !3!3!@!@!L!:     ! !EKLt$//(:;LFL  Ms 0A7"A<cnK|j|g|d{}|j|dS7wrD)rdrHrIs r-_acallzLLMChain._acall.s; kJJ""8,Q//Ks 535c 0||||jS)SFormat prompt with kwargs and pass to LLM. 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Example: .. code-block:: python completion = llm.predict(adjective="funny") rOrr,rOkwargss r-predictzLLMChain.predict6sFi0AAr/c^K|j||d{|jS7w)rrN)acallr4rs r-apredictzLLMChain.apredictGs*jj9j==tOO=s -+-c tjdd|jdd|i|}|jj%|jjj |S|S)z(Call predict and then parse the results.z_The predict_and_parse method is deprecated, instead pass an output parser directly to LLMChain. stacklevelrOr*)warningswarnrr0r6parser,rOrrs r-predict_and_parsezLLMChain.predict_and_parseXsc   B <    B J)<%%f--r/c|jj@|Dcgc]4}|jjj||j6c}S|Scc}wr)r0r6rr4)r,rr_s r-rzLLMChain._parse_generations\ ;; $ $ 0& ))//DOO0DE  s9AcKtjdd|j||d{}|j|S7w)rz^The aapply_and_parse method is deprecated, instead pass an output parser directly to LLMChain.rrrN)rrrrrs r-aapply_and_parsezLLMChain.aapply_and_parsesK   B {{:{CC%%f--Ds.AAAcy)N llm_chainr*r+s r- _chain_typezLLMChain._chain_typesr/c@tj|}|||S)z&Create LLMChain from LLM and template.)r1r0)r from_template)clsr1templateprompt_templates r- from_stringzLLMChain.from_strings!)66x@s?33r/cJt|jj|Sr)_get_language_modelr1get_num_tokens)r,r2s r-_get_num_tokenszLLMChain._get_num_tokenss"488,;;DAAr/)returnr()rz list[str]r)rJdict[str, Any]rF$Optional[CallbackManagerForChainRun]rdict[str, str])r\list[dict[str, Any]]rFrrr)r\rrF)Optional[AsyncCallbackManagerForChainRun]rr)r\rrFrr-tuple[list[PromptValue], Optional[list[str]]])r\rrFrrr)r\rrOrrlist[dict[str, str]])rr3)rrrr)rJrrFrrr)rOrrrrr3)rOrrrrz%Union[str, list[str], dict[str, Any]])rOrrrrz%Union[str, list[str], dict[str, str]])r\rrOrr/Sequence[Union[str, list[str], dict[str, str]]])rrrr)r1rrr3rr')r2r3rint)'__name__ __module__ __qualname____doc__ classmethodr.__annotations__r4r!rr6r7r8r9r model_configpropertyr?rBrLrGrdrSrarrrrHrrrrrrrrrrrr*r/r-r'r''s B  "J).)OM&O#t"PT2J2 $L ++44=A00:0  0=A2(2:2  2<BF2(2?2  2<=A(: 7 8BF(? 7 8 $(  8 $(  2 "BF00?0  0B"P& $ / $ $ / & $ .( . . 9 . (  9  $ .( . . 9 .44 Br/r'cBt|tr|St|trt|jSt|t rt|j St|ttfrt|jSdt|}t|)NzAUnable to extract BaseLanguageModel from llm_like object of type ) rUrrrboundrrunnablerrdefaulttyperp)llm_likervs r-rrs(-.(O,"8>>22(12"8#4#455(^_=>"8#3#344 K >   S/r/)rrrr)4r __future__rrcollections.abcrtypingrrrrlangchain_core._apir langchain_core.callbacksr r r r rlangchain_core.language_modelsrrlangchain_core.messagesrlangchain_core.output_parsersrrlangchain_core.outputsrrrlangchain_core.prompt_valuesrlangchain_core.promptsrrlangchain_core.runnablesrrrr%langchain_core.runnables.configurablerlangchain_core.utils.inputrpydanticr r!langchain.chains.baser"r'rr*r/r-rs8"$--*0NHH4E B7&' 8  ~Bu~B  ~BB r/